Nonparametric Regression and Spline Smoothing (2nd Ed.) Statistics: A Series of Textbooks and Monographs Series
Langue : Anglais
Auteur : Eubank Randall L.
Provides a unified account of the most popular approaches to nonparametric regression smoothing. This edition contains discussions of boundary corrections for trigonometric series estimators; detailed asymptotics for polynomial regression; testing goodness-of-fit; estimation in partially linear models; practical aspects, problems and methods for confidence intervals and bands; local polynomial regression; and form and asymptotic properties of linear smoothing splines.
What is a good estimator?; series estimators; kernel estimators; smoothing splines; least-square splines.
Professional
Randall L. Eubank
'Provides a unified account of the most popular approaches to nonparametric regression smoothing. Second Edition contains new discussions of boundary corrections for trigonometric series estimators
Date de parution : 06-2020
15.6x23.4 cm
Thèmes de Nonparametric Regression and Spline Smoothing :
Mots-clés :
Polynomial Regression Estimators; Nonparametric Regression; function; Local Linear Regression Estimator; true; Kernel Estimators; kernel; Smoothing Spline Fit; estimators; True Regression Function; unbiased; Estimated Fourier Coefficients; risk; Smoothing Spline Estimator; polynomial; Regression Function; linear; Interval Estimators; estimator; Ridge Estimators; cauchy; Smoothing Parameter; Data Set; Unknown Regression Function; Boundary Kernels; Cosine Series; Series Estimator; Quadratic Kernel; Quadratic Splines; Bonferroni Intervals; Linear Estimators; Bayesian Confidence Intervals; Cubic Splines; Truncated Power Basis; Polynomial Regression
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